IJIET 2026 Vol.16(5): 1353-1364
doi: 10.18178/ijiet.2026.16.5.2602
doi: 10.18178/ijiet.2026.16.5.2602
Cognitive Reconfiguration through Brain-Based Learning Based on Digital Ethnoscience to Accelerate Critical Thinking Skills in Elementary School Students
Asriyadin*, Adi Apriadi Adiansha, Anita Nurgufriani, Asri Mulyani,
and Muhammad Fuadi
Elementary School Teacher Education Study Program, STKIP Taman Siswa Bima, Bima, Indonesia
Email: asriyadin@tsb.ac.id (A.); adiapriadiadiansha@tsb.ac.id (A.A.A.); anitanurgufriani@tsb.ac.id (A.N.); asrimulyaniahmad@gmail.com (A.M.); muhammadfuadi@tsb.ac.id (M.F.)
*Corresponding author
Email: asriyadin@tsb.ac.id (A.); adiapriadiadiansha@tsb.ac.id (A.A.A.); anitanurgufriani@tsb.ac.id (A.N.); asrimulyaniahmad@gmail.com (A.M.); muhammadfuadi@tsb.ac.id (M.F.)
*Corresponding author
Manuscript received May 8, 2025; revised June 3, 2025; accepted October 9, 2025; published May 19, 2026
Abstract—This study aims to examine the effectiveness of a digital ethnoscience-based Brain-Based Learning model in improving the critical reasoning skills of elementary school students through cognitive reconfiguration mechanisms. A quantitative approach with a quasi-experimental design (one-group pretest-posttest design) was used on 25 fifth-grade students, with instruments in the form of essay tests developed based on four critical thinking indicators: information analysis, argument evaluation, inference and justification, and alternative solution formulation. Data were analyzed using paired samples t-test, descriptive statistics, and Rasch model to evaluate item suitability and person ability. The results showed a highly significant improvement in all indicators, indicated by extreme t-values and p < 0.001 in every pretest–posttest comparison. Error Bar Plot visualization reinforces these findings with non-overlapping confidence intervals between pre- and post-intervention scores. Rasch analysis supports the consistency of the instrument’s validity, with high person and item reliability, as well as positive logit shifts in student ability. Wright Map and Item Characteristic Curve indicate that the applied learning model encourages stable and discriminative responses to item complexity. Thus, the Brain-Based Learning model based on digital ethnoscience has proven not only to significantly improve learning outcomes but also to promote the restructuring of students’ thinking patterns in building adaptive, contextual, and locally-based critical reasoning. These findings provide important contributions to the development of neuroscience-based pedagogy in the context of elementary education and strategic approaches to critical education at the elementary level.
Keywords—cognitive reconsolidation, brain-based learning, digital ethnoscience, critical thinking, elementary school
Copyright © 2026 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
Keywords—cognitive reconsolidation, brain-based learning, digital ethnoscience, critical thinking, elementary school
Cite: Asriyadin, Adi Apriadi Adiansha, Anita Nurgufriani, Asri Mulyani, and Muhammad Fuadi, "Cognitive Reconfiguration through Brain-Based Learning Based on Digital Ethnoscience to Accelerate Critical Thinking Skills in Elementary School Students," International Journal of Information and Education Technology, vol. 16, no. 5, pp. 1353-1364, 2026.
Copyright © 2026 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).